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Understanding Visual Saliency in Mobile User Interfaces

Luis A. Leiva, Yunfei Xue, Avya Bansal, Hamed R. Tavakoli, Tuðçe Köroðlu, Jingzhou Du, Niraj Ramesh Dayama, Antti Oulasvirta

202078 citationsDOIOpen Access PDF

Abstract

For graphical user interface (UI) design, it is important to understand what attracts visual attention. While previous work on saliency has focused on desktop and web-based UIs, mobile app UIs differ from these in several respects. We present findings from a controlled study with 30 participants and 193 mobile UIs. The results speak to a role of expectations in guiding where users look at. Strong bias toward the top-left corner of the display, text, and images was evident, while bottom-up features such as color or size affected saliency less. Classic, parameter-free saliency models showed a weak fit with the data, and data-driven models improved significantly when trained specifically on this dataset (e.g., NSS rose from 0.66 to 0.84). We also release the first annotated dataset for investigating visual saliency in mobile UIs.

Topics & Concepts

Computer scienceHuman–computer interactionMobile deviceVisual attentionGraphical user interfaceUser interfaceVisualizationInterface (matter)Artificial intelligenceWorld Wide WebPsychologyMaximum bubble pressure methodOperating systemPerceptionBubbleParallel computingProgramming languageNeuroscienceVisual Attention and Saliency DetectionImage and Video Quality AssessmentOlfactory and Sensory Function Studies
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